International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

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 Volume 5, Issue 8 (August 2018), Pages: 104-112

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 Original Research Paper

 Title: Profound correlation of human and NAO-robot interaction through facial expression controlled by EEG sensor

 Author(s): Ahmad Hoirul Basori 1, *, Mohamed Abdulkareem Ahmed 2, Anton Satria Prabuwono 1, 3, Arda Yunianta 1, 4, Arif Bramantoro 1, Irfan Syamsuddin 1, 5, Khalid Hamed Allehaibi 6

 Affiliation(s):

 1Faculty of Computing and Information Technology Rabigh, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia
 2Tikkurila Oyj, Vantaa, Finland
 3Master in Computer Science Program, Budi Luhur University, Jakarta 12260, Indonesia
 4Faculty of Computer Science and Information Technology, Mulawarman University, Indonesia
 5CAIR - Center for Applied ICT Research, Department of Computer and Networking Engineering, School of Electrical Engineering Politeknik Negeri Ujung Pandang, Makassar, Indonesia
 6Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia

 https://doi.org/10.21833/ijaas.2018.08.013

 Full Text - PDF          XML

 Abstract:

Emotion recognition from brain computer interface (EEG) has been studied extensively for the past few years. Time-frequency analysis is widely used in the past research; however, a variation of case study determines the brain signal analysis. In this paper, human emotion from brain waves is recognized in simple ways by calculating a frequency of signal variation. Entirely 35 healthy subjects from students with age 18-25 years old. The students are divided into 3 groups; the first group consists of 15 students; the second group consists of 10 students and the third group consists of 10 students. Each student takes 4 seconds to test his or her internal emotions. The signal speed is recorded during those 4 seconds. Based on stimulus time, various knocks for Z1 and Z2 is observed during a particular time. The experiment can be reproduced for in upcoming future by following the procedure. There are two main elements to measure signal speed which are ΔT and gap. ΔT subject to time differentiation of the changes in time-frequency of Alpha signals. For an evaluation of this work, there is an available benchmark database of EEG labeled with emotions; it mentions that emotional strength can be used as a factor to differentiate between human emotions. The results of this paper can be compared with previous researches which use the same device to differentiate between happy and sad emotions in terms of emotional strength. There is a strong correlation between emotional strength and frequency, we proved that sad feeling is speedier and beyond steady compared to happy since the number of ΔV to Z1 which represents sad emotion of Alpha signals is greater than ΔV to Z2 that represents a happy feeling in the same time period of the interaction process. 

 © 2018 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Facial expression, Brain computer interface, Emotion

 Article History: Received 25 March 2018, Received in revised form 10 June 2018, Accepted 11 June 2018

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2018.08.013

 Citation:

 Basori AH, Ahmed MA, Prabuwono AS et al. (2018). Profound correlation of human and NAO-robot interaction through facial expression controlled by EEG sensor. International Journal of Advanced and Applied Sciences, 5(8): 104-112

 Permanent Link:

 http://www.science-gate.com/IJAAS/2018/V5I8/Basori.html

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